Data products and governance: what IAM teams should take from this

TL;DR: Data professionals report that 44% lack access to the right data, 41% of executives rate their data as substandard, and 33% prioritise timely delivery, according to Collibra. Treating data as a product shifts the problem from raw asset management to governed reuse, which is now central to AI readiness and operational trust.

NHIMG editorial — based on content published by Collibra: Getting started with data products, a practical introduction

By the numbers:

• 44% of data professionals report not having access to the right data needed for their jobs.
• 41% of executives consider their data to be substandard.
• 33% of executives identify timely data delivery as a top priority for data operations improvement.

Questions worth separating out

Q: How should organisations govern access to data products?

A: Start by treating each data product as a governed service with an owner, an access path, and explicit usage conditions.

Q: When do data products improve governance rather than add complexity?

A: They help when the organisation can define ownership, quality expectations, and lifecycle rules consistently.

Q: What do teams get wrong about data marketplaces?

A: They often focus on discovery and ignore accountability.

Practitioner guidance

• Map data products to named owners and lifecycle states Assign an accountable owner, a support boundary, and a deprecation trigger for every published data product so consumers know who answers for change, quality, and retirement.
• Tie access requests to product contracts Require availability, refresh frequency, and usage conditions to be documented before a product is made discoverable in a marketplace or request workflow.
• Review consumption rights on a fixed cadence Re-certify who can consume high-value data products, especially where business-critical reporting, AI training, or third-party sharing is involved.

What's in the full article

Collibra's full blog post covers the operational detail this post intentionally leaves for the source:

• Role-by-role guidance for executive sponsors, program managers, data product owners, and stewards
• Workflow detail for certifying, publishing, and requesting data products inside a governed marketplace
• Platform-specific capabilities for data quality, observability, lineage, and usage analytics
• Examples of how Collibra frames federated governance across data product teams

👉 Read Collibra's practical guide to getting started with data products →

Data products and governance: what IAM teams should take from this?

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